Overview of definition, evaluation, and algorithms of serendipity in recommender systems
Ning Sun · Applied and Computational Engineering · 2023
Over time, recommendation systems are playing an important role in an increasingly wide range of areas, such as paper retrieval sites that can recommend papers or books to users, and shopping sites that can recommend products to users. With the development of recommendation systems, there are many different metrics to measure a good recommendation system, including serendipity. This paper summarizes the definition of serendipity, a review of the metrics for measuring serendipity, and several major serendipity-oriented algorithms and presents conjectures for future research on serendipity. Through the research of some papers, for how to delimit and evaluate recommender systems, experts have mostly focused on the unexpected, and most of them use and optimize collaborative filtering algorithms to achieve and improve serendipity.